--- EXPERIMENT NOTES
--- EXPERIMENT PROPERTIES
#Tue Nov 22 00:07:42 WET 2016
codeml.models=0 1 2 3 7 8
mrbayes.mpich=
mrbayes.ngen=1000000
tcoffee.alignMethod=CLUSTALW2
tcoffee.params=
tcoffee.maxSeqs=0
codeml.bin=codeml
mrbayes.tburnin=2500
codeml.dir=
input.sequences=
mrbayes.pburnin=2500
mrbayes.bin=mb_adops
tcoffee.bin=t_coffee_ADOPS
mrbayes.dir=/usr/bin/
tcoffee.dir=
tcoffee.minScore=3
input.fasta=/opt/ADOPS/3/AcCoAS-PA/input.fasta
input.names=
mrbayes.params=
codeml.params=
--- PSRF SUMMARY
Estimated marginal likelihoods for runs sampled in files
"/opt/ADOPS/3/AcCoAS-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/3/AcCoAS-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run2.p":
(Use the harmonic mean for Bayes factor comparisons of models)
(Values are saved to the file /opt/ADOPS/3/AcCoAS-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.lstat)
Run Arithmetic mean Harmonic mean
--------------------------------------
1 -6712.69 -6728.83
2 -6712.91 -6727.89
--------------------------------------
TOTAL -6712.80 -6728.47
--------------------------------------
Model parameter summaries over the runs sampled in files
"/opt/ADOPS/3/AcCoAS-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run1.p" and "/opt/ADOPS/3/AcCoAS-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.run2.p":
Summaries are based on a total of 3002 samples from 2 runs.
Each run produced 2001 samples of which 1501 samples were included.
Parameter summaries saved to file "/opt/ADOPS/3/AcCoAS-PA/batch/allfiles/mrbayes/input.fasta.fasta.mrb.pstat".
95% HPD Interval
--------------------
Parameter Mean Variance Lower Upper Median min ESS* avg ESS PSRF+
------------------------------------------------------------------------------------------------------
TL{all} 1.122596 0.004176 0.995313 1.245475 1.119862 1487.16 1494.08 1.000
r(A<->C){all} 0.098746 0.000167 0.072965 0.122981 0.098283 1122.87 1236.74 1.000
r(A<->G){all} 0.246898 0.000511 0.204525 0.291708 0.246365 1045.45 1045.85 1.000
r(A<->T){all} 0.096965 0.000298 0.063176 0.130619 0.096562 787.90 816.24 1.000
r(C<->G){all} 0.055907 0.000060 0.041401 0.071458 0.055641 869.42 940.27 1.000
r(C<->T){all} 0.434596 0.000671 0.382403 0.484099 0.434153 884.39 917.87 1.000
r(G<->T){all} 0.066888 0.000119 0.046630 0.089000 0.066423 1082.22 1157.24 1.000
pi(A){all} 0.210251 0.000073 0.193807 0.227382 0.210330 710.92 951.33 1.000
pi(C){all} 0.292525 0.000089 0.273172 0.309998 0.292395 876.28 1053.20 1.000
pi(G){all} 0.289859 0.000094 0.270238 0.307708 0.289600 1127.69 1181.95 1.000
pi(T){all} 0.207364 0.000067 0.191195 0.222970 0.207362 1151.50 1185.05 1.000
alpha{1,2} 0.103220 0.000050 0.089187 0.117402 0.102717 1228.35 1296.16 1.000
alpha{3} 5.085831 1.092732 3.211495 7.152025 4.974179 1335.44 1352.30 1.001
pinvar{all} 0.409523 0.000661 0.357976 0.457102 0.409691 1435.37 1435.93 1.000
------------------------------------------------------------------------------------------------------
* Convergence diagnostic (ESS = Estimated Sample Size); min and avg values
correspond to minimal and average ESS among runs.
ESS value below 100 may indicate that the parameter is undersampled.
+ Convergence diagnostic (PSRF = Potential Scale Reduction Factor; Gelman
and Rubin, 1992) should approach 1.0 as runs converge.
Setting sumt conformat to Simple
--- CODEML SUMMARY
Model 1: NearlyNeutral -6181.540846
Model 2: PositiveSelection -6181.540848
Model 0: one-ratio -6199.828236
Model 3: discrete -6177.589209
Model 7: beta -6181.121194
Model 8: beta&w>1 -6177.575576
Model 0 vs 1 36.57478000000083
Model 2 vs 1 3.99999953515362E-6
Model 8 vs 7 7.091236000000208
Additional information for M7 vs M8:
Naive Empirical Bayes (NEB) analysis
Bayes Empirical Bayes (BEB) analysis (Yang, Wong & Nielsen 2005. Mol. Biol. Evol. 22:1107-1118)
Positively selected sites (*: P>95%; **: P>99%)
(amino acids refer to 1st sequence: D_melanogaster_AcCoAS-PA)
Pr(w>1) post mean +- SE for w
422 Y 0.501 1.211 +- 0.814
